Photon allocation strategy in region-of-interest tomographic imaging

TL;DR

This paper introduces a photon-efficient measurement strategy for region-of-interest CT that significantly reduces reconstruction error at extremely low photon flux levels, optimizing dose and image quality.

Contribution

It proposes a novel photon allocation method that leverages photon statistics for improved ROI reconstruction in low-dose CT, addressing the trade-off between interior quality and exterior dose.

Findings

10-15 fold lower ROI reconstruction error compared to truncated projections

2-fold lower error than whole-volume CT scan

Effective dose reduction at extremely low photon flux (~10 photons per pixel)

Abstract

Photon counting detection is a promising approach toward effectively reducing the radiation dose in x-ray computed tomography (CT). Full CT reconstruction from a fraction of the detected photons required by scintillation-based detectors has been demonstrated. Current efforts in photon-counting CT have focused mainly on reconstruction techniques. In medical and industrial x-ray computed tomography (CT) applications, truncated projection from the region-of-interest (ROI) is another effective way of dose reduction, as information from the ROI is usually sufficient for diagnostic purpose. Projection truncation poses an ill-conditioned inverse problem, which can be improved by including projections from the exterior region. However, this trade-off between the interior reconstruction quality and the additional exterior measurement (extra dose) has not been studied. In this manuscript, we explore the number of detected x-ray photons as a new dimension for measurement engineering. Specifically, we design a flexible, photon-efficient measurement strategy for ROI reconstruction by incorporating the photon statistics at extremely low flux level (~10 photons per pixel). The optimized photon-allocation strategy shows 10 ~ 15-fold lower ROI reconstruction error than truncated projections, and 2-fold lower than whole-volume CT scan. Our analysis in few-photon interior tomography could serve as a new framework for dose-efficient, task-specific x-ray image acquisition design.